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Found 4 papers, 0 papers with code
Variational Quantum Reinforcement Learning via Evolutionary Optimization
Recent advance in classical reinforcement learning (RL) and quantum computation (QC) points to a promising direction of performing RL on a quantum computer.
Detecting transition between Abelian and non-Abelian topological orders through symmetric tensor networks
Furthermore, we show that contrary to the claim in [Phys.
Tensor Networks
Strongly Correlated Electrons
An end-to-end trainable hybrid classical-quantum classifier
We introduce a hybrid model combining a quantum-inspired tensor network and a variational quantum circuit to perform supervised learning tasks.
Hybrid quantum-classical classifier based on tensor network and variational quantum circuit
One key step in performing quantum machine learning (QML) on noisy intermediate-scale quantum (NISQ) devices is the dimension reduction of the input data prior to their encoding.
